CN114531377B - Flow control method, system, equipment and medium for flow industrial equipment data - Google Patents
Flow control method, system, equipment and medium for flow industrial equipment data Download PDFInfo
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Abstract
The method comprises the steps of presetting an information stack for storing flow industrial equipment data, setting a preset cache traffic threshold of the information stack, obtaining the current traffic in the flow industrial equipment data to be uploaded and the information stack, storing the flow industrial equipment data to be uploaded into the information stack if the current traffic is smaller than the preset cache traffic threshold, and sending the flow industrial equipment data with the earliest data time in the information stack to an application server if the time in the information stack is the same as the preset time, wherein even if an emergency such as the rapid increase of the number of communication and service requests occurs, the server is not in downtime in the process of huge communication, storage and calculation demands, and the server is not dragged by unpredictable and continuous processing requests.
Description
Technical Field
The present invention relates to the field of device monitoring technologies, and in particular, to a flow control method, system, device, and medium for flow industrial device data.
Background
Often, the process industry needs a plurality of devices to be implemented together, and the health status of each device has a significant influence on the produced products and the like. Therefore, health status detection needs to be performed on many process industrial equipment in the process industry to ensure that the produced products meet the production requirements, and faults or hidden faults and the like can be found in time. Because the health status of a plurality of process industry devices in the process industry needs to be monitored, the number of sensors matched with each device is also in an ascending trend, and servers (or server clusters) for collecting, storing and processing data are directly oriented to the field to collect network data from bottom to top, the performance and the number of cluster configuration are estimated according to the application requirement trade-offs. When the number of communication and service requests is increased rapidly, the server is down in the process of huge communication, storage and calculation demands, and the server is towed down by unpredictable and continuous processing requests.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the present invention provides a flow control method, system, device and medium for flow industrial equipment data, so as to solve the above-mentioned technical problems.
The invention provides a flow control method of flow industrial equipment data, which is characterized by comprising the following steps:
presetting an information stack for storing flow industrial equipment data, and setting a preset cache traffic threshold of the information stack;
acquiring flow industrial equipment data to be uploaded and current traffic in the information stack, wherein the flow industrial equipment data to be uploaded comprises data time;
if the current traffic is smaller than the preset buffer traffic threshold, storing the to-be-uploaded flow industrial equipment data into the information stack;
and if the time in the stack is the same as the preset time, sending the flow industrial equipment data with the earliest data time in the information stack to an application server.
Optionally, the process industrial equipment data includes data collected by a plurality of sensors, each of the plurality of sensors being one or more in number, the method further comprising:
and if the current traffic is greater than or equal to the preset buffer traffic threshold, respectively acquiring the current transmission rate of each sensor, the size of data to be uploaded of the flow industrial equipment data to be uploaded, the number of sensor types, the number of sensors of each sensor, the data size and preset weight, and determining the adjustment transmission rate of each sensor.
Optionally, the determining manner of the adjustment transmission rate of each sensor includes:
wherein,indicating the adjusted transmission rate, x, of sensor j after adjustment j Indicating the current transmission rate of sensor j, n j Indicating the number of sensors, l, corresponding to the current sensor j j Indicating the data size, n, corresponding to the current sensor j o l o Representing the size of data to be uploaded, max representing a preset buffer traffic threshold value, w j Representing preset weights of the sensors j, # (T) representing the number of sensor types, w 0 The adjustment weight of the sensor j is represented, and the T represents the sensor corresponding to the information stack.
Optionally, the method further comprises at least one of:
discarding the industrial equipment data of the flow to be uploaded if the current traffic is greater than or equal to the preset buffer traffic threshold;
if the time in the stack is different from the preset time, acquiring the current time, and updating the time in the stack through the current time.
Optionally, the determining manner of the preset time includes:
respectively acquiring the initial transmission time of the current transmission data and the preset outflow rate of the information stack;
and determining the preset time according to the initial transmission time and the preset outflow rate.
Optionally, the process industrial equipment data includes data collected by a plurality of sensors, the method further comprising at least one of:
if at least one of the number of sensors, the type of sensors and the transmission rate is changed, determining an adjusted cache traffic threshold according to the preset cache traffic threshold and the changed at least one of the number of sensors, the type of sensors and the transmission rate;
if the bandwidth of the data sent to the application server is changed, determining an adjusted outflow rate according to the changed bandwidth and the preset outflow rate of the information stack.
The invention also provides a flow control system of the flow industrial equipment data, which comprises:
the information stack is used for storing flow industrial equipment data, and is provided with a preset cache traffic threshold;
the acquisition module is used for acquiring the to-be-uploaded process industrial equipment data and the current traffic in the information stack, wherein the to-be-uploaded process industrial equipment data comprises data time;
the first interception module is used for storing the industrial equipment data of the flow to be uploaded into the information stack if the current traffic is smaller than the preset cache traffic threshold;
and the second interception module is used for sending the flow industrial equipment data with the earliest data time in the information stack to an application server if the time in the stack is the same as the preset time.
Optionally, the system further comprises:
a plurality of process industry devices, each process industry device is provided with one or more sensors, and the sensors are used for collecting data of the process industry devices;
the communication module is used for transmitting the flow industrial equipment data to the information stack;
an application server, the application server comprising a plurality of servers.
The invention also provides an electronic device, which comprises a processor, a memory and a communication bus;
the communication bus is used for connecting the processor and the memory;
the processor is configured to execute a computer program stored in the memory to implement the method according to any one of the embodiments described above.
The present invention also provides a computer-readable storage medium, having stored thereon a computer program,
the computer program is configured to cause the computer to perform the method according to any one of the embodiments described above.
The invention has the beneficial effects that: the method comprises the steps of presetting an information stack for storing flow industrial equipment data, setting a preset cache traffic threshold of the information stack, obtaining the current traffic in the flow industrial equipment data to be uploaded and the information stack, storing the flow industrial equipment data to be uploaded into the information stack if the current traffic is smaller than the preset cache traffic threshold, and sending the flow industrial equipment data with the earliest data time in the information stack to an application server if the time in the information stack is the same as the preset time, wherein even if an emergency such as the rapid increase of the number of communication and service requests occurs, the server is not in downtime in the process of huge communication, storage and calculation demands, and the server is not dragged by unpredictable and continuous processing requests.
Drawings
FIG. 1 is a flow diagram of a flow control method for flow industrial equipment data provided in a first embodiment of the present invention;
FIG. 2 is a device block diagram of a flow control system for process industrial device data provided in accordance with a first embodiment of the present invention;
FIG. 3 is a schematic diagram of a flow control system for process industrial equipment data according to a second embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present invention by way of illustration, and only the components related to the present invention are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
In the following description, numerous details are set forth in order to provide a more thorough explanation of embodiments of the present invention, it will be apparent, however, to one skilled in the art that embodiments of the present invention may be practiced without these specific details, in other embodiments, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the embodiments of the present invention.
Example 1
As shown in fig. 1, the present embodiment provides a flow control method for flow industrial equipment data, which includes:
step S101: presetting an information stack for storing flow industrial equipment data, and setting a preset buffer traffic threshold of the information stack.
Alternatively, the information stack may be located between the intelligent device (process industry device) and the server (server cluster, application server) in the field. And acquiring flow industrial equipment data acquired by each sensor of the flow industrial equipment through an information stack, and transmitting the corresponding flow industrial equipment data to an application server under proper conditions so as to supply the application server to perform corresponding data analysis.
The preset buffer traffic threshold may be a value set by one skilled in the art as required. Optionally, the preset buffer traffic threshold may be determined according to at least one of a historical data request amount of the application server, a current transmission bandwidth, a type of the process industrial equipment, a collection frequency of the process industrial equipment data, and the like.
Alternatively, the information stack may be disposed in an edge server (or a control server close to the application server cluster side), where the edge server (or the control server) links all the field intelligent devices (process industrial devices) on one hand, is responsible for communication connection and unpacking of the field intelligent devices, and on the other hand, is responsible for assigning appropriate communication services. The edge server (or the control server) adopts a space with a preset size (preset buffer traffic threshold) inside, and is used for buffering the business (flow industrial equipment data) flowing in by the intelligent field equipment.
The intelligent terminal equipment (process industrial equipment) performs cloud collaboration with the servers (application servers, application server clusters, server clusters and servers) on the Internet cloud through a network, so that the computing capacity and collaborative analysis capacity of the single equipment can be improved. Theoretically, the more the types and the number of the single devices which can access the network are, the more intelligent centralized analysis and overall planning of the cloud server are brought into play, so that the larger and more complex network application is gradually developed. In order to cope with the increase of nodes and traffic in a scene, an information stack is arranged in an edge server (or a control server), and data transmission in the information stack is controlled, so that stable processing of a back-end server is ensured, and the server is prevented from being dragged by unpredictable and continuous processing requests.
Optionally, the intelligent device (process industrial device) may be at least one of a stress wave sensing device, a vibration sensing device, a harmonic sensing device, a pressure sensing device, a temperature sensing device, a rotation speed sensing device, and the like, and each end of the intelligent device (process industrial device) is provided with one or more sensors to collect corresponding process industrial device data.
Optionally, the intelligent device (process industrial device) can operate in a real scene of device health operation and maintenance, and the collected process industrial device data is health monitoring data of each intelligent device.
Step S102: and acquiring current traffic in the industrial equipment data and information stack of the process to be uploaded.
The flow industrial equipment data to be uploaded comprises data time. That is, each data waiting to be uploaded to the information stack is provided with a data time, and based on the data time, the data can be known when the data is acquired, so that the data acquired at a plurality of different times of the same device can be distinguished.
And after uploading the flow industrial equipment data to the information stack and receiving the flow industrial equipment data, the flow industrial equipment data becomes the flow industrial equipment data in the information stack.
The process industry equipment data to be uploaded may be data collected by sensors of the process industry equipment. Since one information stack may correspond to a plurality of process industrial devices, each process industrial device may also be correspondingly provided with one or more sensors, the process industrial device data to be uploaded may be data collected by all sensors, may be data collected by part of the sensors, and the process industrial device data may include data of all process industrial devices, or may be data of part of the process industrial devices. The data collection rules of the sensors of the various process industrial equipment can be preset by a person skilled in the art according to the needs or can be adjusted in a feedback manner based on the residual data capacity of the information stack. The data collection rules of the sensors can be the same or different.
Alternatively, the current traffic in the information stack may be the current amount of capacity stored in the information stack. The data capacity can be the data size of all the currently stored data, the space in the information stack can be divided into a plurality of storage spaces, the data which does not exceed the storage space size in the to-be-uploaded flow industrial equipment data acquired at different times is stored based on the time dimension, and the current traffic can be the number of the currently occupied storage spaces and the like. Correspondingly, the preset buffer traffic threshold may be the data size of all the storage spaces of the information stack, or the total number of the divided storage spaces in the information stack, etc.
Step S103: and if the current traffic is smaller than the preset buffer traffic threshold, storing the industrial equipment data of the flow to be uploaded into an information stack.
The industrial equipment data to be uploaded can be transmitted to the information stack by a wireless gateway or in a wired transmission mode, when the information stack still has blank storage space, the industrial equipment data to be uploaded is stored, otherwise, when the whole storage space of the information stack is used or the residual storage space is smaller than the data size of the industrial equipment data to be uploaded, the industrial equipment data to be uploaded is discarded or stored in a temporary storage space.
Optionally, the information stack discards the traffic (process industrial equipment data) exceeding the buffer space (preset buffer traffic threshold), and the information stack assigns the buffered traffic (process industrial equipment data) to the application server according to a preset outflow rate using a first-in first-out principle similar to "stack".
In one embodiment, the process industrial equipment data includes data collected by a plurality of sensors, each sensor being one or more in number, the method further comprising:
if the current traffic is greater than or equal to a preset buffer traffic threshold, respectively acquiring the current transmission rate of each sensor, the size of data to be uploaded of the industrial equipment data of the flow to be uploaded, the number of sensor types, the number of sensors of each sensor, the data size and preset weight, and determining the adjustment transmission rate of each sensor.
In this case, the process industrial equipment data may include data of a plurality of process industrial equipment, and a process industrial equipment may be provided with a plurality of detection dimensions, that is, a process industrial equipment may be provided with a plurality of sensors, so if a storage space in an information stack is insufficient to store the process industrial equipment data to be uploaded, data collection frequency of each sensor and/or data transmission rate of data collected by the sensors need to be adjusted to reduce energy consumption.
Alternatively, the sensor usually collects data to form the process industrial equipment data to be uploaded to be stored by the information stack, and the current transmission rate and the adjusted transmission rate can be in direct proportion (or equal) to the data collection frequency of the sensor. If the sensor carries a certain data caching space, the data transmission rate of the sensor can be adjusted by adjusting the transmission rate, but the data acquisition frequency of the sensor is not adjusted, so that once equipment is in a problem, the data which are not uploaded before can be extracted based on the data caching space of the sensor, and the sources of fault data are enriched. In other words, the adjustment transmission rate may be only the data transmission rate of the sensor, or may be the data transmission rate and the data acquisition frequency of the sensor.
In one embodiment, the determining manner of the adjustment transmission rate of each sensor includes:
wherein,indicating the adjusted transmission rate, x, of sensor j after adjustment j Indicating the current transmission rate of sensor j, n j Indicating the number of sensors, l, corresponding to the current sensor j j Indicating the data size, n, corresponding to the current sensor j o l o Representing the size of data to be uploaded, max representing a preset buffer traffic threshold value, w j Representing preset weights of the sensors j, # (T) representing the number of sensor types, w 0 The adjustment weight of the sensor j is represented, and the T represents the sensor corresponding to the information stack.
In one embodiment, the current traffic M may be determined by the following formula:
M＝∑ j∈T n j l j formula (2);
wherein M is the current traffic, T is the sensor corresponding to (connected with) the information stack, n j Indicating the number of sensors, l, corresponding to the current sensor j j Indicating the data size corresponding to the current sensor j.
In another embodiment, the current traffic M may be determined by the following formula:
M＝∑ j∈T n j l j +n o l o formula (3);
wherein M is the current traffic, T is the sensor corresponding to (connected with) the information stack, n j Indicating the number of sensors, l, corresponding to the current sensor j j Indicating the data size, n, corresponding to the current sensor j o l o Representing process industrial equipment data to be uploaded.
Step S104: and if the time in the stack is the same as the preset time, sending the process industrial equipment data with the earliest data time in the information stack to an application server.
Alternatively, the same time in the stack as the preset time may be understood as reaching a certain preset interval time. In other words, the information stack transmits data once every certain time interval.
Because each wave has data time to be uploaded to the process industrial equipment data, the process industrial equipment data currently cached in the information stack can be ordered based on the data time, and the process industrial equipment data with earliest time is sent to the application server.
Alternatively, the application server may be a plurality of single servers, or may exist in a server cluster.
Alternatively, the information stack may transmit process industrial equipment data to the equipment health detection system based on the internet so that the system detects the health status of each of the equipment.
Alternatively, the information stack may transmit the process industrial equipment data to at least one of equipment asset management systems, data collection systems, data analysis systems, health detection systems, data twinning, and the like, including but not limited to, based on the internet. Alternatively, the device asset management system, data acquisition system, data analysis system, health detection system, data twinning may be integrated into one or more health management application server clusters.
In one embodiment, the method further comprises at least one of:
if the current traffic is greater than or equal to a preset buffer traffic threshold, discarding the industrial equipment data of the process to be uploaded;
if the time in the stack is different from the preset time, acquiring the current time, and updating the time in the stack through the current time.
Alternatively, the time in the stack may be the count of a time counter built into the information stack.
Optionally, the determining manner of the preset time includes:
respectively acquiring the initial transmission time of the current transmission data and the preset outflow rate of an information stack;
and determining the preset time according to the initial transmission time and the preset outflow rate.
The initial transmission time may be a real time, and the time interval may be obtained according to the preset outflow rate, and the addition of the initial propagation time and the time interval is performed to obtain the preset time. For example, the initial transmission time is 12:01:05, the preset outflow rate is 5 s/time, and the current preset time is 12:01:10.
Alternatively, the initial transmission time may be 0, and the time interval may be obtained according to the preset outflow rate, and the addition of the initial propagation time and the time interval is performed to obtain the preset time. For example, the initial transmission time is 0, the preset outflow rate is 5 s/time, and the current preset time is 5. At this time, the time in the stack is also a count of 0 initially.
In one embodiment, the process industrial equipment data comprises data collected by a plurality of sensors, the method further comprising at least one of:
if at least one of the number of sensors, the type of sensors and the transmission rate is changed, determining an adjusted cache traffic threshold according to the preset cache traffic threshold and at least one of the changed number of sensors, the type of sensors and the transmission rate, for example, adjusting the cache traffic threshold in proportion to the change of the number of sensors, the type of sensors and the transmission rate;
if the bandwidth of the data sent to the application server changes, the adjusted outflow rate is determined according to the changed bandwidth and the preset outflow rate of the information stack, if the bandwidth is increased, the preset outflow rate is increased to be used as the adjusted outflow rate, and the adjusted outflow rate can be obtained by proportionally adjusting the preset outflow rate according to the change of the bandwidth.
The above embodiment provides a flow control method of flow industrial equipment data, which is to compare, through a preset information stack, based on a current traffic in the current information stack and a preset buffer traffic threshold value to determine whether to store the flow industrial equipment data to be uploaded, if there is still a residual space in the information stack, then store, otherwise discard the flow industrial equipment data to be uploaded. And sending the flow industrial equipment data with the earliest data time in the information stack to an application server by controlling according to the time. By adopting the information stack with the preset size of space, the business flowed in by the intelligent equipment is cached, and the business exceeding the cache space is abandoned, and the caching business is distributed to the application server according to the preset outflow rate by adopting the first-in first-out principle similar to a stack. The method can ensure that the application server is not damaged by the increased business.
Optionally, the size of the buffer (preset buffer traffic threshold) and the rate of leakage (outflow rate) are comprehensively considered according to the traffic (data volume of the to-be-uploaded process industrial equipment data), the network speed (bandwidth) and the processing performance of the application server, and are preset by a person skilled in the art. After the environment is changed, a person skilled in the art can manually update the preset value, so that the flow control method operates under the new parameters, and the method maintains good adaptability under different intelligent equipment scales, server hardware performances and network environments.
In the following, by way of a specific embodiment, an exemplary flow control method for the above-mentioned flow industrial equipment data is described, referring to fig. 2, fig. 2 is a block diagram of a flow control system for flow industrial equipment data in the related art, referring to fig. 2, where flow control (information stack) stores and distributes received flow industrial equipment data collected by sensors of each intelligent device to an equipment health detection system according to the flow control method. The sensor comprises one or more sensors arranged on stress wave sensing equipment, vibration sensing equipment, harmonic sensing equipment, pressure sensing equipment, temperature sensing equipment, rotating speed sensing equipment and the like. The process industry equipment data can be transmitted to the information stack via the wireless gateway based on the internet. The device health detection system includes, but is not limited to, at least one of a device asset management system, a data acquisition system, a data analysis system, a health detection system, a data twinning, and the like.
The following illustrates the steps of the flow control method in one example:
(1) The flow system manager initializes the information stack Msg according to the traffic and application server performance conditions]Presetting a buffer traffic threshold Number Max And preset outflow rate Time Max Then starting a flow control method;
(2) The flow control method can be realized through two While loops, and one loop LoopA is used for processing a service processing request from the intelligent field device (used for monitoring and acquiring industrial equipment data of a flow to be uploaded and judging whether buffering is performed or not); another loop LoopB is used to dispatch the service to the application server (determine whether to send the process industrial equipment data with the earliest data time in the information stack to the application server);
(3) The LoopA will always monitor the service processing request from the on-site intelligent device, and execute the judgment of whether the new service (the process industrial device data to be uploaded) is stored by the information stack at the best: number of current traffic Number buf Whether the Number of the upper buffer limit (preset buffer traffic threshold) is reached Max If not, at Msg [ Number ] buf ]Inserting a new business data (to be uploaded process industrial equipment data) and simultaneously Number buf Increment 1; discarding the service data if the service data is full;
(4) The LoopB will always determine if the earliest stacked traffic needs to be dispatched to the application server: counter Time buf Whether or not to equal the outflow rate timer Time Max Equal to, the oldest piece of service information Msg [0 ]]Dispatch to application server while counter Time buf Set to 0, number buf Decrementing 1, msg[]Is shifted forward by one bit, i.e. Msg [ n ]]＝Msg[n+1]The method comprises the steps of carrying out a first treatment on the surface of the If not, updating the counter with the current clock;
(5) If the administrator updates the preset parameters, the flow control method will reinitialize the information stack Msg with the new parameters]Presetting a buffer traffic threshold Number Max And preset outflow rate Time Max And synchronizing the data of the existing information stack to the new Msg]LoopA and LoopB are then started. The updating of the preset parameters may be: when the Number of the bottom devices (the Number of sensors) (n) and the transmission rate (x) are changed, the capacity scale of the information stack, that is, the Number, may need to be readjusted according to the situation Max The method comprises the steps of carrying out a first treatment on the surface of the If the bandwidth changes, it may be necessary to adjust the outflow rate, i.e. Time Max Thereby optimizing performance.
Alternatively, the data transmission of the process industrial equipment with the earliest data time in the information stack to the application server may be implemented by a message management system of Kafka (high throughput distributed publish-subscribe message system), the data coming out of the information stack enters Kafka, the data subscribed by each application system on the upper layer on Kafka, kafka is responsible for data distribution, and the Kafka may be a concurrent processing on subscription requests.
In one embodiment, if the amount of the incoming data (to-be-uploaded process industrial equipment data) exceeds the information stack capacity (preset buffer traffic threshold), the transmission rate is automatically reversely adjusted according to the preset weights of the various sensors. In x 1 ,x 2 ,x 3 ,…,x k Indicating the transmission rate of the sensor, l 1 ,l 2 ,l 3 ,…,l k Representing the sensor data size, w 1 ,w 2 ,w 3 ,…,w k Indicating that the sensor corresponds to a preset weight. The current traffic M is calculated as shown in equation (3).
M＝∑ j∈T n j l j Formula (4)
Wherein T represents a sensor in the barrel, n 1 ,n 2 ,n 3 ,…,n j Indicating the number of sensors corresponding to the current barrel. When sigma j∈T n j l j +n o l o When the transmission speed x is less than or equal to max j J epsilon T does not make any adjustment, n o l o Representing the data in the next incoming information stack (flow industrial equipment data to be uploaded). When sigma j∈T n j l j +n o l o >At max, the transmission speed x j The adjustment mode of j epsilon T is shown in a formula (4).
Wherein,indicating the adjusted transmission rate, x, of sensor j after adjustment j Indicating the current transmission rate of sensor j, n j Indicating the number of sensors, l, corresponding to the current sensor j j Indicating the data size, n, corresponding to the current sensor j o l o Representing the size of data to be uploaded, max representing a preset buffer traffic threshold value, w j Representing preset weights of the sensors j, # (T) representing the number of sensor types, w 0 The adjustment weight of the sensor j is represented, and the T represents the sensor corresponding to the information stack.
The method can ensure the stability of the application server not to be damaged by the increased business, and simultaneously, the size of the buffer and the leakage rate are preset in advance according to comprehensive consideration of the business volume, the network speed and the processing performance of the application server. After the environment is changed, the preset value can be updated, so that the flow control method can be operated under the new parameters, and the good adaptability of the method under different intelligent equipment scales, server hardware performances and network environments is maintained.
Example two
Referring to fig. 3, the present embodiment provides a flow control system 300 for flow industrial equipment data, comprising:
an information stack 301, configured to store process industrial equipment data, where the information stack is set with a preset buffer traffic threshold;
the acquiring module 302 is configured to acquire to-be-uploaded process industrial equipment data and current traffic in an information stack, where the to-be-uploaded process industrial equipment data includes data time;
the first interception module 303 is configured to store the process industrial equipment data to be uploaded into the information stack if the current traffic is less than a preset buffer traffic threshold;
and the second interception module 304 is configured to send the process industrial equipment data with the earliest data time in the information stack to the application server if the time in the stack is the same as the preset time.
Optionally, the system further comprises:
a plurality of process industrial devices, each process industrial device being provided with one or more sensors for acquiring process industrial device data;
the communication module is used for transmitting the flow industrial equipment data to the information stack;
and the application server comprises a plurality of servers.
In this embodiment, the system is essentially provided with a plurality of modules for executing the method in the above embodiment, and specific functions and technical effects are only needed with reference to the above embodiment, and are not repeated herein.
Referring to fig. 4, an embodiment of the present invention also provides an electronic device 600 comprising a processor 601, a memory 602 and a communication bus 603;
a communication bus 603 for connecting the processor 601 and the memory 602;
the processor 601 is configured to execute a computer program stored in the memory 602 to implement the method as described in one or more of the above embodiments.
The embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored,
the computer program is for causing a computer to execute the method according to any one of the above embodiments.
The embodiment of the present application further provides a non-volatile readable storage medium, where one or more modules (programs) are stored, where the one or more modules are applied to a device, and the device may be caused to execute instructions (instructions) of a step included in the embodiment one of the embodiment of the present application.
It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.
Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The above embodiments are merely illustrative of the principles of the present invention and its effectiveness, and are not intended to limit the invention. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the invention. Accordingly, it is intended that all equivalent modifications and variations of the invention be covered by the claims, which are within the ordinary skill of the art, be within the spirit and scope of the present disclosure.
Claims (8)
1. A method of flow control of process industrial equipment data, the method comprising:
presetting an information stack for storing flow industrial equipment data, and setting a preset cache traffic threshold of the information stack;
acquiring flow industrial equipment data to be uploaded and current traffic in the information stack, wherein the flow industrial equipment data to be uploaded comprises data time;
if the current traffic is smaller than the preset buffer traffic threshold, storing the to-be-uploaded flow industrial equipment data into the information stack;
the flow industrial equipment data comprises data acquired by a plurality of sensors, the number of each sensor is one or more, if the current traffic is greater than or equal to the preset buffer traffic threshold value, the current transmission rate of each sensor is respectively acquired, the size of the data to be uploaded of the flow industrial equipment data to be uploaded, the number of sensor types, the number of sensors, the data size and preset weight of each sensor are respectively acquired, the adjustment transmission rate of each sensor is determined, and the flow industrial equipment data is transmitted to the information stack;
if the time in the stack is the same as the preset time, sending the flow industrial equipment data with the earliest data time in the information stack to an application server;
the determining mode of the adjustment transmission rate of each sensor comprises the following steps:
wherein,indicating the adjusted transmission rate, x, of sensor j after adjustment j Indicating the current transmission rate of sensor j, n j Indicating the number of sensors, l, corresponding to the current sensor j j Indicating the data size, n, corresponding to the current sensor j o l o Representing the size of data to be uploaded, max representing a preset buffer traffic threshold value, w j Representing preset weights of the sensors j, # (T) representing the number of sensor types, w 0 The adjustment weight of the sensor j is represented, and the T represents the sensor corresponding to the information stack.
2. The method of claim 1, wherein the method further comprises at least one of:
discarding the industrial equipment data of the flow to be uploaded if the current traffic is greater than or equal to the preset buffer traffic threshold;
if the time in the stack is different from the preset time, acquiring the current time, and updating the time in the stack through the current time.
3. The method of claim 1, wherein the predetermined time is determined by:
respectively acquiring the initial transmission time of the current transmission data and the preset outflow rate of the information stack;
and determining the preset time according to the initial transmission time and the preset outflow rate.
4. The method of claim 1, wherein the process industrial equipment data comprises data collected by a plurality of sensors, the method further comprising at least one of:
if at least one of the number of sensors, the type of sensors and the transmission rate is changed, determining an adjusted cache traffic threshold according to the preset cache traffic threshold and the changed at least one of the number of sensors, the type of sensors and the transmission rate;
if the bandwidth of the data sent to the application server is changed, determining an adjusted outflow rate according to the changed bandwidth and the preset outflow rate of the information stack.
5. A flow control system for process industrial equipment data, the system comprising:
the information stack is used for storing flow industrial equipment data, and is provided with a preset cache traffic threshold;
the acquisition module is used for acquiring the to-be-uploaded process industrial equipment data and the current traffic in the information stack, wherein the to-be-uploaded process industrial equipment data comprises data time;
the first interception module is used for storing the industrial equipment data of the flow to be uploaded into the information stack if the current traffic is smaller than the preset cache traffic threshold;
the system comprises a plurality of process industrial equipment, a plurality of data transmission rate control unit, a data transmission unit and a data transmission unit, wherein each process industrial equipment is provided with one or more sensors, the sensors are used for acquiring process industrial equipment data, the process industrial equipment data comprise data acquired by a plurality of sensors, the number of each sensor is one or more, if the current traffic is greater than or equal to the preset buffer traffic threshold value, the current transmission rate of each sensor is respectively acquired, the size of data to be uploaded of the process industrial equipment data to be uploaded, the number of sensor types, the number of sensors, the data size and preset weight of each sensor are respectively acquired, and the adjustment transmission rate of each sensor is determined;
the communication module is used for transmitting the flow industrial equipment data to the information stack;
the second interception module is used for sending the flow industrial equipment data with the earliest data time in the information stack to an application server if the time in the stack is the same as the preset time;
the determining mode of the adjustment transmission rate of each sensor comprises the following steps:
wherein,indicating the adjusted transmission rate, x, of sensor j after adjustment j Indicating the current transmission rate of sensor j, n j Indicating the number of sensors, l, corresponding to the current sensor j j Indicating the data size, n, corresponding to the current sensor j o l o Representing the size of data to be uploaded, max representing a preset buffer traffic threshold value, w j Representing preset weights of the sensors j, # (T) representing the number of sensor types, w 0 The adjustment weight of the sensor j is represented, and the T represents the sensor corresponding to the information stack.
6. The system of claim 5, wherein the system further comprises:
an application server, the application server comprising a plurality of servers.
7. An electronic device comprising a processor, a memory, and a communication bus;
the communication bus is used for connecting the processor and the memory;
the processor is configured to execute a computer program stored in the memory to implement the method of any one of claims 1-4.
8. A computer-readable storage medium, having a computer program stored thereon,
the computer program for causing the computer to perform the method of any one of claims 1-4.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1684464A1 (en) * | 2005-01-24 | 2006-07-26 | Alcatel | Traffic management and monitoring in communications networks |
| CN108769162A (en) * | 2018-05-16 | 2018-11-06 | 上海携程商务有限公司 | Distributed message equalization processing method, device, electronic equipment, storage medium |
| CN109885399A (en) * | 2019-01-17 | 2019-06-14 | 平安普惠企业管理有限公司 | Data processing method, electronic device, computer equipment and storage medium |
| CN110401720A (en) * | 2019-07-31 | 2019-11-01 | 中国工商银行股份有限公司 | Information processing method, device, system, application server and medium |
| WO2020026013A1 (en) * | 2018-07-31 | 2020-02-06 | 优视科技新加坡有限公司 | Data transmission method, apparatus and device/terminal/server and computer readable storage medium |
| CN110932997A (en) * | 2019-12-09 | 2020-03-27 | 苏州浪潮智能科技有限公司 | Method, device and medium for reducing network traffic packet loss |
| WO2021004063A1 (en) * | 2019-07-11 | 2021-01-14 | 网宿科技股份有限公司 | Cache server bandwidth scheduling method and device |
| CN113242184A (en) * | 2021-06-10 | 2021-08-10 | 京东科技控股股份有限公司 | Flow control method of distributed architecture and related equipment |
-
2022
- 2022-01-19 CN CN202210059096.3A patent/CN114531377B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1684464A1 (en) * | 2005-01-24 | 2006-07-26 | Alcatel | Traffic management and monitoring in communications networks |
| CN108769162A (en) * | 2018-05-16 | 2018-11-06 | 上海携程商务有限公司 | Distributed message equalization processing method, device, electronic equipment, storage medium |
| WO2020026013A1 (en) * | 2018-07-31 | 2020-02-06 | 优视科技新加坡有限公司 | Data transmission method, apparatus and device/terminal/server and computer readable storage medium |
| CN109885399A (en) * | 2019-01-17 | 2019-06-14 | 平安普惠企业管理有限公司 | Data processing method, electronic device, computer equipment and storage medium |
| WO2021004063A1 (en) * | 2019-07-11 | 2021-01-14 | 网宿科技股份有限公司 | Cache server bandwidth scheduling method and device |
| CN110401720A (en) * | 2019-07-31 | 2019-11-01 | 中国工商银行股份有限公司 | Information processing method, device, system, application server and medium |
| CN110932997A (en) * | 2019-12-09 | 2020-03-27 | 苏州浪潮智能科技有限公司 | Method, device and medium for reducing network traffic packet loss |
| CN113242184A (en) * | 2021-06-10 | 2021-08-10 | 京东科技控股股份有限公司 | Flow control method of distributed architecture and related equipment |
Non-Patent Citations (1)
| Title |
|---|
| 串行网络中ABR业务的流量控制和缓存设计;杨根科,吴智铭,曾建潮;通信学报(第01期);全文 * |
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